Literature DB >> 33672222

Preliminary Investigation on Systems for the Preventive Diagnosis of Faults on Agricultural Operating Machines.

Massimo Cecchini1, Francesca Piccioni1, Serena Ferri1, Gianluca Coltrinari1, Leonardo Bianchini1, Andrea Colantoni1.   

Abstract

This paper aims to investigate failures induced by vibrations on machines, focusing on agricultural ones. The research on literature has brought to light a considerable amount of data on the driven vehicles and not much on the operating machines, including the ones that we looked for. For this reason, it was decided to direct a survey with the people who work with agricultural machinery every day: operators, sub-contractors, and producers. They were asked about the most frequent breakage, particularly in relation to the rotary harrow, the topic of this work. The questionnaire results showed the types of failures the harrow is most vulnerable to, indicating the times of failure and reparation and the need to set up a potentially useful preventive maintenance supporting system on these machines. Part of the work was then focused on the proposition of a method to investigate bearing failures in the rotary harrow, considering that these have been analyzed in the technical literature and in the survey as the most at-risk components. The proposed method in this work serves as a beginning for the development of a future on board sent-shore-based maintenance system for continuous monitoring of the bearing.

Entities:  

Keywords:  crack; damage detection; failure; fatigue; ultrasonic; vibration

Year:  2021        PMID: 33672222     DOI: 10.3390/s21041547

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions.

Authors:  Andreas Holzinger; Anna Saranti; Alessa Angerschmid; Carl Orge Retzlaff; Andreas Gronauer; Vladimir Pejakovic; Francisco Medel-Jimenez; Theresa Krexner; Christoph Gollob; Karl Stampfer
Journal:  Sensors (Basel)       Date:  2022-04-15       Impact factor: 3.847

  1 in total

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